Results 11 to 20 of about 1,504,339 (298)
Neural logic programs and neural nets
CoRRNeural-symbolic integration aims to combine the connectionist subsymbolic with the logical symbolic approach to artificial intelligence. In this paper, we first define the answer set semantics of (boolean) neural nets and then introduce from first principles a class of neural logic programs and show that nets and programs are equivalent.
Antić, Christian
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IET Intelligent Transport Systems, 2023 Rail transit has many advantages, such as large passenger capacity, convenience, safety, and environmental protection, making it the preferred travel mode for most passengers.
Xuanrong Zhang +3 more
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SRI3D: Two‐stream inflated 3D ConvNet based on sparse regularization for action recognition
IET Image Processing, 2023 Although most state‐of‐the‐art action recognition models have adopted a two‐stream 3D convolutional structure as a backbone network, few works have studied the impact of loss functions on action recognition models.
Zhaoqilin Yang +4 more
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Temporal Modeling of Neural Net Input/Output Behaviors: The Case of XOR
Systems, 2017 In the context of the modeling and simulation of neural nets, we formulate definitions for the behavioral realization of memoryless functions. The definitions of realization are substantively different for deterministic and stochastic systems constructed
Bernard P. Zeigler, Alexandre Muzy
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Predictions models with neural nets
Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis, 2008 The contribution is oriented to basic problem trends solution of economic pointers, using neural networks. Problems include choice of the suitable model and consequently configuration of neural nets, choice computational function of neurons and the way ...
Vladimír Konečný
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Quantum speed-up in global optimization of binary neural nets
New Journal of Physics, 2021 The performance of a neural network (NN) for a given task is largely determined by the initial calibration of the network parameters. Yet, it has been shown that the calibration, also referred to as training, is generally NP-complete.
Yidong Liao +3 more
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Two Algebraic Process Semantics for Contextual Nets
, 2001 We show that the so-called 'Petri nets are monoids' approach initiated by Meseguer and Montanari can be extended from ordinary place/transition Petri nets to contextual nets by considering suitable non-free monoids of places.
SASSONE V. +5 more
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CN-Nets for modeling and analyzing neural networks [PDF]
, 2001 he concept of colored timed neural Petri nets (CTNPN or Shortly eN-net) which are isomorphic to neural architectures is proposed. The CN-net technique incorporates the basic features of the neural net and the modeling capabilities of both colored and ...
Samir M. Koriem, Koriem, Samir M.
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Functorial Models for Petri Nets [PDF]
, 2001 We show that although the algebraic semantics of place/transition Petri nets under the collective token philosophy can be fully explained in terms of strictly symmetric monoidal categories, the analogous construction under the individual token philosophy
Meseguer, J. +3 more
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Scientific Reports, 2022 Deep neural network (DNN) and Convolution neural network (CNN) algorithms have significantly increased the accuracies in cutting-edge large-scale image recognition and natural-language processing tasks.
Varun Bheemireddy
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